An Improved Mechanism to Maintain Data Integrity and Anomaly Detection in Cloud Storage
Aditi Joshi
Department of Computer Science and Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Delhi, NCR Campus, Modinagar, Ghaziabad, Uttar Pradesh, India.
Department of Computer Science and Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Delhi, NCR Campus, Modinagar, Ghaziabad, Uttar Pradesh, India.
There are different services which can be offered by cloud platforms such as Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS). These services and resources are provided by the third party and available on-demand through the Internet. It enables the organizations to focus on the infrastructure and services rather than maintain it. It includes several challenges such as vendor lock-in, security, data integrity, and compliance issues. To address these issues is very challenging for organizations and relies on cloud services. However, data integrity is one of the critical challenges due to data inconsistency, user trust, completeness, and compliance. Therefore, to ensure the data integrity distinct mechanisms can be applied such as encryption, access control, regular audits, backups, and data validations. The integration of these strategies results in a comprehensive framework for maintaining data integrity in cloud storage, ensuring trustworthiness, security, and compliance with regulatory standards. The result set indicates the higher accuracy approximate 1.0 with good number of instances of benign and suspicious data. The major aim of the current research is to enhance the security of cloud data by using AES algorithms and provide double encryption. The extraction of the top features by using recursive feature elimination. Finally, AI-powered anomaly detection is proposed for data integrity and to detect anomalous access patterns, unauthorized changes, and suspicious transactions in real-time, helping prevent integrity violations before they escalate.
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CRediT Author Statement
The authors confirm contribution to the paper as follows:
Conceptualization: Aditi Joshi, Rajendra Prasad Mahapatra and Ganesh Gopal Devarajan;
Methodology: Aditi Joshi and Rajendra Prasad Mahapatra;
Software: Rajendra Prasad Mahapatra and Ganesh Gopal Devarajan;
Data Curation: Aditi Joshi and Rajendra Prasad Mahapatra;
Writing- Original Draft Preparation: Aditi Joshi, Rajendra Prasad Mahapatra and Ganesh Gopal Devarajan;
Visualization: Rajendra Prasad Mahapatra and Ganesh Gopal Devarajan;
Investigation: Aditi Joshi and Rajendra Prasad Mahapatra;
Supervision: Rajendra Prasad Mahapatra and Ganesh Gopal Devarajan;
Validation: Aditi Joshi and Rajendra Prasad Mahapatra;
Writing- Reviewing and Editing: Aditi Joshi, Rajendra Prasad Mahapatra and Ganesh Gopal Devarajan;
All authors reviewed the results and approved the final version of the manuscript.
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Corresponding author
Ganesh Gopal Devarajan
Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Noida, Uttar Pradesh, India.
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Cite this article
Aditi Joshi, Rajendra Prasad Mahapatra and Ganesh Gopal Devarajan, “An Improved Mechanism to Maintain Data Integrity and Anomaly Detection in Cloud Storage”, Journal of Machine and Computing, vol.6, no.1, pp. 296-311, 2026, doi: 10.53759/7669/jmc202606022.
